949 resultados para road weather information system
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Highway agencies spend millions of dollars to ensure safe and efficient winter travel. However, the effectiveness of winter-weather maintenance practices on safety and mobility are somewhat difficult to quantify. Safety and Mobility Impacts of Winter Weather - Phase 1 investigated opportunities for improving traffic safety on state-maintained roads in Iowa during winter-weather conditions. In Phase 2, three Iowa Department of Transportation (DOT) high-priority sites were evaluated and realistic maintenance and operations mitigation strategies were also identified. In this project, site prioritization techniques for identifying roadway segments with the potential for safety improvements related to winter-weather crashes, were developed through traditional naïve statistical methods by using raw crash data for seven winter seasons and previously developed metrics. Additionally, crash frequency models were developed using integrated crash data for four winter seasons, with the objective of identifying factors that affect crash frequency during winter seasons and screening roadway segments using the empirical Bayes technique. Based on these prioritization techniques, 11 sites were identified and analyzed in conjunction with input from Iowa DOT district maintenance managers and snowplow operators and the Iowa DOT Road Weather Information System (RWIS) coordinator.
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Friction plays a key role in causing slipperiness as a low coefficient of friction on the road may result in slippery and hazardous conditions. Analyzing the strong relation between friction and accident risk on winter roads is a difficult task. Many weather forecasting organizations use a variety of standard and bespoke methods to predict the coefficient of friction on roads. This article proposes an approach to predict the extent of slipperiness by building and testing an expert system. It estimates the coefficient of friction on winter roads in the province of Dalarna, Sweden using the prevailing weather conditions as a basis. Weather data from the road weather information system, Sweden (RWIS) was used. The focus of the project was to use the expert system as a part of a major project in VITSA, within the domain of intelligent transport systems
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The goal of this research project was to develop a method to measure the performance of a winter maintenance program with respect to the task of providing safety and mobility to the travelling public. Developing these measures required a number of steps, each of which was accomplished. First, the impact of winter weather on safety (crash rates) and mobility (average vehicle speeds were measured by a combination of literature reviews and analysis of Iowa Department of Transportation traffic and Road Weather Information System data. Second, because not all winter storms are the same in their effects on safety and mobility, a method had to be developed to determine how much the various factors that describe a winter storm actually change safety and mobility. As part of this effort a storm severity index was developed, which ranks each winter storm on a scale between 0 (a very benign storm) and 1 (the worst imaginable storm). Additionally a number of methods of modeling the relationships between weather, winter maintenance actions and road surface conditions were developed and tested. The end result of this study was a performance measure based on average vehicle speed. For a given class of road, a maximum expected average speed reduction has been identified. For a given storm, this maximum expected average speed reduction is modified by the storm severity index to give a target average speed reduction. Thus, if for a given road the maximum expected average speed reduction is 20 mph, and the storm severity for a particular storm is 0.6, then the target average speed reduction for that road in that storm is 0.6 x 20 mph or 12 mph. If the average speed on that road during and after the storm is only 12 mph or less than the average speed on that road in good weather conditions, then the winter maintenance performance goal has been met.
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Transport is an essential sector in modern societies. It connects economic sectors and industries. Next to its contribution to economic development and social interconnection, it also causes adverse impacts on the environment and results in health hazards. Transport is a major source of ground air pollution, especially in urban areas, and therefore contributing to the health problems, such as cardiovascular and respiratory diseases, cancer, and physical injuries. This thesis presents the results of a health risk assessment that quantifies the mortality and the diseases associated with particulate matter pollution resulting from urban road transport in Hai Phong City, Vietnam. The focus is on the integration of modelling and GIS approaches in the exposure analysis to increase the accuracy of the assessment and to produce timely and consistent assessment results. The modelling was done to estimate traffic conditions and concentrations of particulate matters based on geo-references data. A simplified health risk assessment was also done for Ha Noi based on monitoring data that allows a comparison of the results between the two cases. The results of the case studies show that health risk assessment based on modelling data can provide a much more detail results and allows assessing health impacts of different mobility development options at micro level. The use of modeling and GIS as a common platform for the integration of different assessments (environmental, health, socio-economic, etc.) provides various strengths, especially in capitalising on the available data stored in different units and forms and allows handling large amount of data. The use of models and GIS in a health risk assessment, from a decision making point of view, can reduce the processing/waiting time while providing a view at different scales: from micro scale (sections of a city) to a macro scale. It also helps visualising the links between air quality and health outcomes which is useful discussing different development options. However, a number of improvements can be made to further advance the integration. An improved integration programme of the data will facilitate the application of integrated models in policy-making. Data on mobility survey, environmental monitoring and measuring must be standardised and legalised. Various traffic models, together with emission and dispersion models, should be tested and more attention should be given to their uncertainty and sensitivity
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Objective: To demonstrate the potential of GIS (geographic information system) technology and ARIA (Accessibility/Remoteness Index for Australia) as tools for medical workforce and health service planning in Australia. Design: ARIA is an index of remoteness derived by measuring road distance between populated localities and service centres. A continuous variable of remoteness from 0 to 12 is generated for any location in Australia. We created a GIS, with data on location of general practitioner services in non-metropolitan South Australia derived from the database of HUMPS (Rural Undergraduate Medical Placement System), and estimated, for the 1170 populated localities in South Australia, the accessibility/inaccessibility of the 109 identified GP services. Main outcome measures: Distance from populated locality to GP services. Results: Distance from populated locality to GP service ranged from 0 to 677 km (mean, 58 km). In all, 513 localities (43%) had a GP service within 20 km (for the majority this meant located within the town). However, for 173 populated localities (15%), the nearest GP service was more than 80 km away. There was a strong correlation between distance to GP service and ARIA value for each locality (0.69; P<0.05). Conclusions: GP services are relatively inaccessible to many rural South Australian communities. There is potential for GIS and for ARIA to contribute to rational medical workforce and health service planning. Adding measures of health need and more detailed data on types and extent of GP services provided will allow more sophisticated planning.
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OBJECTIVE To describe heterogeneity of HIV prevalence among pregnant women in Hlabisa health district, South Africa and to correlate this with proximity of homestead to roads. METHODS HIV prevalence measured through anonymous surveillance among pregnant women and stratified by local village clinic. Polygons were created around each clinic, assuming women attend the clinic nearest their home. A geographical information system (GIS) calculated the mean distance from homesteads in each clinic catchment to nearest primary (1 degrees) and to nearest primary or secondary (2 degrees) road. RESULTS We found marked HIV heterogeneity by clinic catchment (range 19-31% (P < 0.001). A polygon plot demonstrated lower HIV prevalence in catchments remote from 1 degrees roads. Mean distance from homesteads to nearest 1 degrees or 2 degrees road varied by clinic catchment from 1623 to 7569 m. The mean distance from homesteads to a 1 degrees or 2 degrees road for each clinic catchment was strongly correlated with HIV prevalence (r = 0.66; P = 0.002). CONCLUSIONS The substantial HIV heterogeneity in this district is closely correlated with proximity to a 1 degrees or 2 degrees road. GIS is a powerful tool to demonstrate and to start to analyse this observation. Further research is needed to better understand this relationship both at ecological and individual levels, and to develop interventions to reduce the spread of HIV infection.
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This project was proposed as Phase I of a 2-phase program to evaluate the present use of weather information by Iowa Department of Transportation (IaDOT) personnel, recommend revised procedures, and then implement the resulting recommendations. Midway through Phase I (evaluation phase) the FORETELL project was funded. This project is a multi-state venture that engages the National Weather Service (NWS) and the Forecast Systems Laboratory of the National Oceanic and Atmospheric Administration and proposes to supplant the current weather information-generation and distribution system with an advanced system based on state-of-the-art technologies. The focus of the present project was therefore refined to consider use of weather data by IaDOT personnel, and the training programs needed to more effectively use these data. Results of the survey revealed that two major areas - training of personnel on use of data from whatever source and more precise information of frost formation - are not addressed in the FORETELL project. These aspects have been the focus of the present project.
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A network of 25 sonic stage sensors were deployed in the Squaw Creek basin upstream from Ames Iowa to determine if the state-of-the-art distributed hydrological model CUENCAS can produce reliable information for all road crossings including those that cross small creeks draining basins as small as 1 sq. mile. A hydraulic model was implemented for the major tributaries of the Squaw Creek where IFC sonic instruments were deployed and it was coupled to CUENCAS to validate the predictions made at small tributaries in the basin. This study demonstrates that the predictions made by the hydrological model at internal locations in the basins are as accurate as the predictions made at the outlet of the basin. Final rating curves based on surveyed cross sections were developed for the 22 IFC-bridge sites that are currently operating, and routine forecast is provided at those locations (see IFIS). Rating curves were developed for 60 additional bridge locations in the basin, however, we do not use those rating curves for routine forecast because the lack of accuracy of LiDAR derived cross sections is not optimal. The results of our work form the basis for two papers that have been submitted for publication to the Journal of Hydrological Engineering. Peer review of our work will gives a strong footing to our ability to expand our results from the pilot Squaw Creek basin to all basins in Iowa.
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ABSTRACT Geographic Information System (GIS) is an indispensable software tool in forest planning. In forestry transportation, GIS can manage the data on the road network and solve some problems in transportation, such as route planning. Therefore, the aim of this study was to determine the pattern of the road network and define transport routes using GIS technology. The present research was conducted in a forestry company in the state of Minas Gerais, Brazil. The criteria used to classify the pattern of forest roads were horizontal and vertical geometry, and pavement type. In order to determine transport routes, a data Analysis Model Network was created in ArcGIS using an Extension Network Analyst, allowing finding a route shorter in distance and faster. The results showed a predominance of horizontal geometry classes average (3) and bad (4), indicating presence of winding roads. In the case of vertical geometry criterion, the class of highly mountainous relief (4) possessed the greatest extent of roads. Regarding the type of pavement, the occurrence of secondary coating was higher (75%), followed by primary coating (20%) and asphalt pavement (5%). The best route was the one that allowed the transport vehicle travel in a higher specific speed as a function of road pattern found in the study.
Integrated motorist information system (IMIS) feasibility and design study : phase 1 : feasibility /
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Mode of access: Internet.
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The road to electric rope shovel automation is marked with technological innovations that include an increase in operational information available to mining operations. The CRCMining Shovel Operator Information System not only collects machine operational data but also provides the operator with knowledge-of-performance and influences his/her performance to achieve higher productivity with reduced machine duty. The operator’s behaviour is one of the most important aspects of the man-machine interaction to be considered before semi- or fully-automated shovel systems can be realised. This paper presents the results of the rope shovel studies conducted by CRCMining between 2002 and 2004, provides information on current research to improve shovel performance and briefly discusses the implications of human-system interactions on future designs of autonomous machines.
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With the exponential increasing demands and uses of GIS data visualization system, such as urban planning, environment and climate change monitoring, weather simulation, hydrographic gauge and so forth, the geospatial vector and raster data visualization research, application and technology has become prevalent. However, we observe that current web GIS techniques are merely suitable for static vector and raster data where no dynamic overlaying layers. While it is desirable to enable visual explorations of large-scale dynamic vector and raster geospatial data in a web environment, improving the performance between backend datasets and the vector and raster applications remains a challenging technical issue. This dissertation is to implement these challenging and unimplemented areas: how to provide a large-scale dynamic vector and raster data visualization service with dynamic overlaying layers accessible from various client devices through a standard web browser, and how to make the large-scale dynamic vector and raster data visualization service as rapid as the static one. To accomplish these, a large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling and a comprehensive performance improvement solution are proposed, designed and implemented. They include: the quadtree-based indexing and parallel map tiling, the Legend String, the vector data visualization with dynamic layers overlaying, the vector data time series visualization, the algorithm of vector data rendering, the algorithm of raster data re-projection, the algorithm for elimination of superfluous level of detail, the algorithm for vector data gridding and re-grouping and the cluster servers side vector and raster data caching.
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To assess the completeness and reliability of the Information System on Live Births (Sinasc) data. A cross-sectional analysis of the reliability and completeness of Sinasc's data was performed using a sample of Live Birth Certificate (LBC) from 2009, related to births from Campinas, Southeast Brazil. For data analysis, hospitals were grouped according to category of service (Unified National Health System, private or both), 600 LBCs were randomly selected and the data were collected in LBC-copies through mothers and newborns' hospital records and by telephone interviews. The completeness of LBCs was evaluated, calculating the percentage of blank fields, and the LBCs agreement comparing the originals with the copies was evaluated by Kappa and intraclass correlation coefficients. The percentage of completeness of LBCs ranged from 99.8%-100%. For the most items, the agreement was excellent. However, the agreement was acceptable for marital status, maternal education and newborn infants' race/color, low for prenatal visits and presence of birth defects, and very low for the number of deceased children. The results showed that the municipality Sinasc is reliable for most of the studied variables. Investments in training of the professionals are suggested in an attempt to improve system capacity to support planning and implementation of health activities for the benefit of maternal and child population.
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El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.
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The purpose is to present a scientific research that led to the modeling of an information system which aimed at the maintenance of traceability data in the Brazilian wine industry, according to the principles of a service-oriented architecture (SOA). Since 2005, traceability data maintenance is an obligation for all producers that intend to export to any European Union country. Also, final customers, including the Brazilian ones, have been asking for information about food products. A solution that collectively contemplated the industry was sought in order to permit that producer consortiums of associations could share the costs and benefits of such a solution. Following an extensive bibliographic review, a series of interviews conducted with Brazilian researchers and wine producers in Bento Goncalves - RS, Brazil, elucidated many aspects associated with the wine production process. Information technology issues related to the theme were also researched. The software was modeled with the Unified Modeling Language (UML) and uses web services for data exchange. A model for the wine production process was also proposed. A functional prototype showed that the adopted model is able to fulfill the demands of wine producers. The good results obtained lead us to consider the use of this model in other domains.